/home/tony/Work/glockenspiel/s3prl/s3prl/upstream/byol_s/byol_a/common.py:20: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend("sox_io")
2023-10-05 00:23:11 | WARNING | root | Pytorch pre-release version 2.1.0.dev20230831+cu118 - assuming intent to test it
/home/tony/Work/glockenspiel/s3prl/s3prl/run_downstream.py:157: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend('sox_io')
2023-10-05 00:23:15 | INFO | fairseq.models.hubert.hubert | HubertModel Config: HubertConfig(_name='hubert', label_rate=50.0, extractor_mode='default', encoder_layers=12, encoder_embed_dim=768, encoder_ffn_embed_dim=3072, encoder_attention_heads=12, activation_fn='gelu', layer_type='transformer', dropout=0.1, attention_dropout=0.1, activation_dropout=0.0, encoder_layerdrop=0.05, dropout_input=0.1, dropout_features=0.1, final_dim=256, untie_final_proj=True, layer_norm_first=False, conv_feature_layers='[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 3', conv_bias=False, logit_temp=0.1, target_glu=False, feature_grad_mult=0.1, mask_length=10, mask_prob=0.8, mask_selection='static', mask_other=0.0, no_mask_overlap=False, mask_min_space=1, mask_channel_length=10, mask_channel_prob=0.0, mask_channel_selection='static', mask_channel_other=0.0, no_mask_channel_overlap=False, mask_channel_min_space=1, conv_pos=128, conv_pos_groups=16, conv_pos_batch_norm=False, latent_temp=[2.0, 0.5, 0.999995], skip_masked=False, skip_nomask=False, checkpoint_activations=False, required_seq_len_multiple=2, depthwise_conv_kernel_size=31, attn_type='', pos_enc_type='abs', fp16=False)
/home/tony/anaconda3/envs/suno_env/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
  warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
2023-10-05 00:23:16 | INFO | fairseq.models.hubert.hubert | cannot find dictionary. assume will be used for fine-tuning
[Featurizer] - Take a list of 2 features and weighted sum them.
[Featurizer] - The selected feature hidden_states's downsample rate is 960
[Runner] - Start a new experiment
mert_test_8x_400k_hubert {'model_config': None, 'refresh': False}
Loading model from Local mert_test_8x_400k_hubert
load local model succeed
load local feat extractor
Wav2Vec2FeatureExtractor {
  "do_normalize": false,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 24000
}

load hubert model succeed

overall:   0%|          | 0/4000 [00:00<?, ?it/s][LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 1995.94it/s]


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train:   4%|▍         | 156/3515 [00:54<19:41,  2.84it/s]
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train:   5%|▍         | 159/3515 [00:55<20:42,  2.70it/s]
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train:   5%|▍         | 160/3515 [00:56<17:56,  3.12it/s]
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train:   5%|▍         | 164/3515 [00:57<18:35,  3.00it/s]
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train:   5%|▍         | 166/3515 [00:58<17:01,  3.28it/s]
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train:  28%|██▊       | 983/3515 [05:38<14:43,  2.87it/s]
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train:  28%|██▊       | 994/3515 [05:42<14:35,  2.88it/s]
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train:  28%|██▊       | 995/3515 [05:43<15:09,  2.77it/s]
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train:  28%|██▊       | 996/3515 [05:43<15:38,  2.68it/s]
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train:  28%|██▊       | 997/3515 [05:43<15:03,  2.79it/s]
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train:  28%|██▊       | 998/3515 [05:44<15:12,  2.76it/s]
overall:  25%|██▍       | 999/4000 [05:47<18:15,  2.74it/s]

train:  28%|██▊       | 999/3515 [05:44<15:18,  2.74it/s]train loss: 4.400906562805176
train per: 0.9389504804138951
train loss: 2.28031849861145
train per: 0.5326138708141565
train loss: 1.3816720247268677
train per: 0.32454746828362385
train loss: 1.151538610458374
train per: 0.2755804456889511
train loss: 1.095941185951233
train per: 0.26377505093097076
train loss: 1.1121717691421509
train per: 0.2566208895048507
train loss: 1.0817477703094482
train per: 0.2608380567849471
train loss: 0.9715433120727539
train per: 0.23636675992735484
train loss: 1.0769041776657104
train per: 0.24953529264004018
train loss: 0.9887398481369019
train per: 0.2361177368571701
train loss: 0.923289954662323
train per: 0.2262423714036617
train loss: 0.9298049807548523
train per: 0.22309644019580205
train loss: 1.0162442922592163
train per: 0.23942173080769122
train loss: 0.9870487451553345
train per: 0.2271554091158704
train loss: 0.9633456468582153
train per: 0.2305223829280033
train loss: 0.9457107782363892
train per: 0.22158057698923675
train loss: 1.039670705795288
train per: 0.24577610638761718
train loss: 0.9737790822982788
train per: 0.23207453868776515
train loss: 0.9175569415092468
train per: 0.219832387418448
train loss: 0.9768377542495728
train per: 0.22836137071651091
train loss: 0.9082286953926086
train per: 0.22219171243135297
train loss: 0.9563080072402954
train per: 0.22685299491383143
train loss: 0.9530431032180786
train per: 0.22464965701478345
train loss: 0.9438020586967468
train per: 0.2229089229551103
train loss: 0.8932175636291504
train per: 0.20944063312182443
train loss: 0.9134238958358765
train per: 0.21631495457385955
train loss: 0.9926717877388
train per: 0.22818899074200757
train loss: 0.9265430569648743
train per: 0.22274768192566222
train loss: 0.8864052891731262
train per: 0.21246251564307808
train loss: 0.8641527891159058
train per: 0.2097708140723079
train loss: 0.9289742708206177
train per: 0.21846688141735454
train loss: 0.9441248178482056
train per: 0.22004085065481196
train loss: 0.848921000957489
train per: 0.2038471623006698
train loss: 0.9198246002197266
train per: 0.21721939067035403
train loss: 0.8669164776802063
train per: 0.20736054895864048
train loss: 0.9502062797546387
train per: 0.22585754719430812
train loss: 0.8660025596618652
train per: 0.2089706017034527
train loss: 0.9440181851387024
train per: 0.225854048917121
train loss: 0.8810156583786011
train per: 0.21105981778657093
train loss: 0.9020352363586426
train per: 0.21553530852213815
train loss: 0.9195740818977356
train per: 0.21636653191228714
train loss: 0.8954803347587585
train per: 0.21342836637216325
train loss: 0.8966845273971558
train per: 0.21088902571875148
train loss: 0.9480964541435242
train per: 0.2227360671983389
train loss: 0.8903528451919556
train per: 0.218275971567454
train loss: 0.8512875437736511
train per: 0.20337650210109848
train loss: 0.8839390873908997
train per: 0.2129057294120908
train loss: 0.8873383402824402
train per: 0.21767561178038783
train loss: 0.9160432815551758
train per: 0.2147551758133421
train loss: 0.8856848478317261
train per: 0.20958097395243488
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:   8%|▊         | 228/2703 [00:00<00:01, 2225.21it/s]


word -> phonemes:  17%|█▋        | 451/2703 [00:00<00:01, 2159.82it/s]


word -> phonemes:  25%|██▍       | 668/2703 [00:00<00:00, 2139.09it/s]


word -> phonemes:  33%|███▎      | 882/2703 [00:00<00:00, 1917.84it/s]


word -> phonemes:  40%|███▉      | 1077/2703 [00:00<00:00, 1918.12it/s]


word -> phonemes:  48%|████▊     | 1307/2703 [00:00<00:00, 2018.17it/s]


word -> phonemes:  56%|█████▋    | 1525/2703 [00:00<00:00, 2067.18it/s]


word -> phonemes:  64%|██████▍   | 1733/2703 [00:00<00:00, 2031.74it/s]


word -> phonemes:  73%|███████▎  | 1973/2703 [00:00<00:00, 2141.67it/s]


word -> phonemes:  82%|████████▏ | 2209/2703 [00:01<00:00, 2206.89it/s]


word -> phonemes:  90%|█████████ | 2446/2703 [00:01<00:00, 2255.45it/s]


word -> phonemes:  99%|█████████▉| 2673/2703 [00:01<00:00, 2179.06it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2115.05it/s]



dev:   0%|          | 0/2703 [00:00<?, ?it/s]


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dev:   4%|▍         | 119/2703 [00:08<02:38, 16.26it/s]


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dev:   5%|▍         | 123/2703 [00:08<02:44, 15.73it/s]


dev:   5%|▍         | 125/2703 [00:08<02:49, 15.21it/s]


dev:   5%|▍         | 127/2703 [00:08<02:44, 15.64it/s]


dev:   5%|▍         | 129/2703 [00:08<02:37, 16.32it/s]


dev:   5%|▍         | 132/2703 [00:08<02:28, 17.33it/s]


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dev:   5%|▌         | 136/2703 [00:09<02:27, 17.42it/s]


dev:   5%|▌         | 139/2703 [00:09<02:16, 18.79it/s]


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overall:  47%|████▋     | 1896/4000 [13:10<10:28,  3.35it/s]

train:  54%|█████▍    | 1896/3515 [13:07<08:03,  3.35it/s]
overall:  47%|████▋     | 1897/4000 [13:10<10:21,  3.38it/s]

train:  54%|█████▍    | 1897/3515 [13:08<07:58,  3.38it/s]
overall:  47%|████▋     | 1898/4000 [13:11<11:22,  3.08it/s]

train:  54%|█████▍    | 1898/3515 [13:08<08:45,  3.08it/s]
overall:  47%|████▋     | 1899/4000 [13:11<11:31,  3.04it/s]

train:  54%|█████▍    | 1899/3515 [13:08<08:52,  3.04it/s]
overall:  48%|████▊     | 1900/4000 [13:12<11:54,  2.94it/s]

train:  54%|█████▍    | 1900/3515 [13:09<09:09,  2.94it/s]
overall:  48%|████▊     | 1901/4000 [13:12<12:18,  2.84it/s]

train:  54%|█████▍    | 1901/3515 [13:09<09:28,  2.84it/s]
overall:  48%|████▊     | 1903/4000 [13:12<10:34,  3.31it/s]

train:  54%|█████▍    | 1903/3515 [13:09<08:07,  3.31it/s]
overall:  48%|████▊     | 1904/4000 [13:13<11:05,  3.15it/s]

train:  54%|█████▍    | 1904/3515 [13:10<08:31,  3.15it/s]
overall:  48%|████▊     | 1905/4000 [13:13<11:48,  2.96it/s]

train:  54%|█████▍    | 1905/3515 [13:10<09:04,  2.96it/s]
overall:  48%|████▊     | 1906/4000 [13:14<11:55,  2.93it/s]

train:  54%|█████▍    | 1906/3515 [13:11<09:09,  2.93it/s]
overall:  48%|████▊     | 1907/4000 [13:14<12:18,  2.84it/s]

train:  54%|█████▍    | 1907/3515 [13:11<09:27,  2.84it/s]
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train:  54%|█████▍    | 1908/3515 [13:11<09:42,  2.76it/s]
overall:  48%|████▊     | 1909/4000 [13:15<12:40,  2.75it/s]

train:  54%|█████▍    | 1909/3515 [13:12<09:43,  2.75it/s]
overall:  48%|████▊     | 1910/4000 [13:15<12:20,  2.82it/s]

train:  54%|█████▍    | 1910/3515 [13:12<09:28,  2.82it/s]
overall:  48%|████▊     | 1911/4000 [13:15<12:43,  2.74it/s]

train:  54%|█████▍    | 1911/3515 [13:12<09:46,  2.74it/s]
overall:  48%|████▊     | 1912/4000 [13:16<12:54,  2.70it/s]

train:  54%|█████▍    | 1912/3515 [13:13<09:54,  2.70it/s]
overall:  48%|████▊     | 1913/4000 [13:16<12:19,  2.82it/s]

train:  54%|█████▍    | 1913/3515 [13:13<09:27,  2.82it/s]
overall:  48%|████▊     | 1914/4000 [13:16<12:25,  2.80it/s]

train:  54%|█████▍    | 1914/3515 [13:14<09:31,  2.80it/s]
overall:  48%|████▊     | 1915/4000 [13:17<12:22,  2.81it/s]

train:  54%|█████▍    | 1915/3515 [13:14<09:29,  2.81it/s]
overall:  48%|████▊     | 1916/4000 [13:17<12:08,  2.86it/s]

train:  55%|█████▍    | 1916/3515 [13:14<09:19,  2.86it/s]
overall:  48%|████▊     | 1917/4000 [13:18<12:28,  2.78it/s]

train:  55%|█████▍    | 1917/3515 [13:15<09:34,  2.78it/s]
overall:  48%|████▊     | 1918/4000 [13:18<12:19,  2.82it/s]

train:  55%|█████▍    | 1918/3515 [13:15<09:26,  2.82it/s]
overall:  48%|████▊     | 1919/4000 [13:18<12:02,  2.88it/s]

train:  55%|█████▍    | 1919/3515 [13:15<09:13,  2.88it/s]
overall:  48%|████▊     | 1920/4000 [13:19<11:56,  2.90it/s]

train:  55%|█████▍    | 1920/3515 [13:16<09:09,  2.90it/s]
overall:  48%|████▊     | 1921/4000 [13:19<12:53,  2.69it/s]

train:  55%|█████▍    | 1921/3515 [13:16<09:52,  2.69it/s]
overall:  48%|████▊     | 1922/4000 [13:19<13:08,  2.63it/s]

train:  55%|█████▍    | 1922/3515 [13:16<10:04,  2.63it/s]
overall:  48%|████▊     | 1923/4000 [13:20<12:57,  2.67it/s]

train:  55%|█████▍    | 1923/3515 [13:17<09:55,  2.67it/s]
overall:  48%|████▊     | 1924/4000 [13:20<12:34,  2.75it/s]

train:  55%|█████▍    | 1924/3515 [13:17<09:38,  2.75it/s]
overall:  48%|████▊     | 1925/4000 [13:20<12:53,  2.68it/s]

train:  55%|█████▍    | 1925/3515 [13:18<09:52,  2.68it/s]
overall:  48%|████▊     | 1926/4000 [13:21<12:45,  2.71it/s]

train:  55%|█████▍    | 1926/3515 [13:18<09:46,  2.71it/s]
overall:  48%|████▊     | 1927/4000 [13:21<12:03,  2.86it/s]

train:  55%|█████▍    | 1927/3515 [13:18<09:14,  2.86it/s]
overall:  48%|████▊     | 1928/4000 [13:21<11:49,  2.92it/s]

train:  55%|█████▍    | 1928/3515 [13:19<09:03,  2.92it/s]
overall:  48%|████▊     | 1929/4000 [13:22<12:07,  2.85it/s]

train:  55%|█████▍    | 1929/3515 [13:19<09:16,  2.85it/s]
overall:  48%|████▊     | 1930/4000 [13:22<12:04,  2.86it/s]

train:  55%|█████▍    | 1930/3515 [13:19<09:14,  2.86it/s]
overall:  48%|████▊     | 1931/4000 [13:22<10:41,  3.23it/s]

train:  55%|█████▍    | 1931/3515 [13:19<08:10,  3.23it/s]
overall:  48%|████▊     | 1932/4000 [13:23<11:06,  3.10it/s]

train:  55%|█████▍    | 1932/3515 [13:20<08:29,  3.10it/s]
overall:  48%|████▊     | 1933/4000 [13:23<11:13,  3.07it/s]

train:  55%|█████▍    | 1933/3515 [13:20<08:35,  3.07it/s]
overall:  48%|████▊     | 1934/4000 [13:23<10:54,  3.15it/s]

train:  55%|█████▌    | 1934/3515 [13:20<08:21,  3.15it/s]
overall:  48%|████▊     | 1935/4000 [13:24<11:31,  2.99it/s]

train:  55%|█████▌    | 1935/3515 [13:21<08:49,  2.99it/s]
overall:  48%|████▊     | 1936/4000 [13:24<10:58,  3.14it/s]

train:  55%|█████▌    | 1936/3515 [13:21<08:23,  3.14it/s]
overall:  48%|████▊     | 1937/4000 [13:24<11:16,  3.05it/s]

train:  55%|█████▌    | 1937/3515 [13:21<08:37,  3.05it/s]
overall:  48%|████▊     | 1938/4000 [13:25<11:38,  2.95it/s]

train:  55%|█████▌    | 1938/3515 [13:22<08:54,  2.95it/s]
overall:  48%|████▊     | 1939/4000 [13:25<12:05,  2.84it/s]

train:  55%|█████▌    | 1939/3515 [13:22<09:14,  2.84it/s]
overall:  48%|████▊     | 1940/4000 [13:25<12:19,  2.79it/s]

train:  55%|█████▌    | 1940/3515 [13:23<09:25,  2.79it/s]
overall:  49%|████▊     | 1941/4000 [13:26<12:36,  2.72it/s]

train:  55%|█████▌    | 1941/3515 [13:23<09:38,  2.72it/s]
overall:  49%|████▊     | 1942/4000 [13:26<12:21,  2.78it/s]

train:  55%|█████▌    | 1942/3515 [13:23<09:26,  2.78it/s]
overall:  49%|████▊     | 1943/4000 [13:27<12:00,  2.85it/s]

train:  55%|█████▌    | 1943/3515 [13:24<09:10,  2.85it/s]
overall:  49%|████▊     | 1944/4000 [13:27<12:05,  2.83it/s]

train:  55%|█████▌    | 1944/3515 [13:24<09:14,  2.83it/s]
overall:  49%|████▊     | 1945/4000 [13:27<13:02,  2.63it/s]

train:  55%|█████▌    | 1945/3515 [13:24<09:57,  2.63it/s]
overall:  49%|████▊     | 1946/4000 [13:28<13:10,  2.60it/s]

train:  55%|█████▌    | 1946/3515 [13:25<10:03,  2.60it/s]
overall:  49%|████▊     | 1947/4000 [13:28<12:43,  2.69it/s]

train:  55%|█████▌    | 1947/3515 [13:25<09:43,  2.69it/s]
overall:  49%|████▊     | 1948/4000 [13:28<12:33,  2.72it/s]

train:  55%|█████▌    | 1948/3515 [13:26<09:35,  2.72it/s]
overall:  49%|████▊     | 1949/4000 [13:29<12:37,  2.71it/s]

train:  55%|█████▌    | 1949/3515 [13:26<09:38,  2.71it/s]
overall:  49%|████▉     | 1950/4000 [13:29<12:42,  2.69it/s]

train:  55%|█████▌    | 1950/3515 [13:26<09:42,  2.69it/s]
overall:  49%|████▉     | 1951/4000 [13:30<12:50,  2.66it/s]

train:  56%|█████▌    | 1951/3515 [13:27<09:47,  2.66it/s]
overall:  49%|████▉     | 1952/4000 [13:30<12:34,  2.72it/s]

train:  56%|█████▌    | 1952/3515 [13:27<09:35,  2.72it/s]
overall:  49%|████▉     | 1953/4000 [13:30<12:50,  2.66it/s]

train:  56%|█████▌    | 1953/3515 [13:27<09:47,  2.66it/s]
overall:  49%|████▉     | 1954/4000 [13:31<12:23,  2.75it/s]

train:  56%|█████▌    | 1954/3515 [13:28<09:26,  2.75it/s]
overall:  49%|████▉     | 1955/4000 [13:31<09:49,  3.47it/s]

train:  56%|█████▌    | 1955/3515 [13:28<07:29,  3.47it/s]
overall:  49%|████▉     | 1956/4000 [13:31<10:24,  3.27it/s]

train:  56%|█████▌    | 1956/3515 [13:28<07:56,  3.27it/s]
overall:  49%|████▉     | 1957/4000 [13:31<11:02,  3.08it/s]

train:  56%|█████▌    | 1957/3515 [13:29<08:25,  3.08it/s]
overall:  49%|████▉     | 1958/4000 [13:32<11:13,  3.03it/s]

train:  56%|█████▌    | 1958/3515 [13:29<08:33,  3.03it/s]
overall:  49%|████▉     | 1959/4000 [13:32<11:40,  2.91it/s]

train:  56%|█████▌    | 1959/3515 [13:29<08:54,  2.91it/s]
overall:  49%|████▉     | 1960/4000 [13:33<11:58,  2.84it/s]

train:  56%|█████▌    | 1960/3515 [13:30<09:07,  2.84it/s]
overall:  49%|████▉     | 1961/4000 [13:33<12:28,  2.72it/s]

train:  56%|█████▌    | 1961/3515 [13:30<09:30,  2.72it/s]
overall:  49%|████▉     | 1962/4000 [13:33<12:10,  2.79it/s]

train:  56%|█████▌    | 1962/3515 [13:30<09:16,  2.79it/s]
overall:  49%|████▉     | 1963/4000 [13:33<09:43,  3.49it/s]

train:  56%|█████▌    | 1963/3515 [13:30<07:24,  3.49it/s]
overall:  49%|████▉     | 1964/4000 [13:34<10:16,  3.30it/s]

train:  56%|█████▌    | 1964/3515 [13:31<07:49,  3.30it/s]
overall:  49%|████▉     | 1965/4000 [13:34<10:41,  3.17it/s]

train:  56%|█████▌    | 1965/3515 [13:31<08:08,  3.17it/s]
overall:  49%|████▉     | 1966/4000 [13:34<11:15,  3.01it/s]

train:  56%|█████▌    | 1966/3515 [13:32<08:34,  3.01it/s]
overall:  49%|████▉     | 1967/4000 [13:35<11:23,  2.97it/s]

train:  56%|█████▌    | 1967/3515 [13:32<08:40,  2.97it/s]
overall:  49%|████▉     | 1968/4000 [13:35<11:48,  2.87it/s]

train:  56%|█████▌    | 1968/3515 [13:32<08:59,  2.87it/s]
overall:  49%|████▉     | 1969/4000 [13:36<12:42,  2.66it/s]

train:  56%|█████▌    | 1969/3515 [13:33<09:40,  2.66it/s]
overall:  49%|████▉     | 1970/4000 [13:36<12:08,  2.79it/s]

train:  56%|█████▌    | 1970/3515 [13:33<09:14,  2.79it/s]
overall:  49%|████▉     | 1971/4000 [13:36<12:19,  2.74it/s]

train:  56%|█████▌    | 1971/3515 [13:33<09:22,  2.74it/s]
overall:  49%|████▉     | 1972/4000 [13:37<12:00,  2.81it/s]

train:  56%|█████▌    | 1972/3515 [13:34<09:08,  2.81it/s]
overall:  49%|████▉     | 1973/4000 [13:37<12:16,  2.75it/s]

train:  56%|█████▌    | 1973/3515 [13:34<09:20,  2.75it/s]
overall:  49%|████▉     | 1974/4000 [13:37<12:15,  2.75it/s]

train:  56%|█████▌    | 1974/3515 [13:34<09:19,  2.75it/s]
overall:  49%|████▉     | 1975/4000 [13:38<12:22,  2.73it/s]

train:  56%|█████▌    | 1975/3515 [13:35<09:24,  2.73it/s]
overall:  49%|████▉     | 1976/4000 [13:38<11:37,  2.90it/s]

train:  56%|█████▌    | 1976/3515 [13:35<08:50,  2.90it/s]
overall:  49%|████▉     | 1977/4000 [13:38<12:10,  2.77it/s]

train:  56%|█████▌    | 1977/3515 [13:36<09:15,  2.77it/s]
overall:  49%|████▉     | 1978/4000 [13:39<12:22,  2.72it/s]

train:  56%|█████▋    | 1978/3515 [13:36<09:24,  2.72it/s]
overall:  49%|████▉     | 1979/4000 [13:39<12:29,  2.70it/s]

train:  56%|█████▋    | 1979/3515 [13:36<09:29,  2.70it/s]
overall:  50%|████▉     | 1980/4000 [13:40<12:45,  2.64it/s]

train:  56%|█████▋    | 1980/3515 [13:37<09:41,  2.64it/s]
overall:  50%|████▉     | 1981/4000 [13:40<12:39,  2.66it/s]

train:  56%|█████▋    | 1981/3515 [13:37<09:36,  2.66it/s]
overall:  50%|████▉     | 1982/4000 [13:40<12:40,  2.65it/s]

train:  56%|█████▋    | 1982/3515 [13:37<09:37,  2.65it/s]
overall:  50%|████▉     | 1983/4000 [13:41<10:28,  3.21it/s]

train:  56%|█████▋    | 1983/3515 [13:38<07:57,  3.21it/s]
overall:  50%|████▉     | 1984/4000 [13:41<10:57,  3.06it/s]

train:  56%|█████▋    | 1984/3515 [13:38<08:19,  3.06it/s]
overall:  50%|████▉     | 1985/4000 [13:41<11:34,  2.90it/s]

train:  56%|█████▋    | 1985/3515 [13:38<08:47,  2.90it/s]
overall:  50%|████▉     | 1986/4000 [13:42<11:38,  2.89it/s]

train:  57%|█████▋    | 1986/3515 [13:39<08:49,  2.89it/s]
overall:  50%|████▉     | 1987/4000 [13:42<11:33,  2.90it/s]

train:  57%|█████▋    | 1987/3515 [13:39<08:46,  2.90it/s]
overall:  50%|████▉     | 1988/4000 [13:42<11:18,  2.96it/s]

train:  57%|█████▋    | 1988/3515 [13:39<08:35,  2.96it/s]
overall:  50%|████▉     | 1989/4000 [13:43<11:36,  2.89it/s]

train:  57%|█████▋    | 1989/3515 [13:40<08:48,  2.89it/s]
overall:  50%|████▉     | 1990/4000 [13:43<11:40,  2.87it/s]

train:  57%|█████▋    | 1990/3515 [13:40<08:51,  2.87it/s]
overall:  50%|████▉     | 1991/4000 [13:43<11:49,  2.83it/s]

train:  57%|█████▋    | 1991/3515 [13:40<08:58,  2.83it/s]
overall:  50%|████▉     | 1992/4000 [13:44<11:35,  2.89it/s]

train:  57%|█████▋    | 1992/3515 [13:41<08:47,  2.89it/s]
overall:  50%|████▉     | 1993/4000 [13:44<12:19,  2.71it/s]

train:  57%|█████▋    | 1993/3515 [13:41<09:20,  2.71it/s]
overall:  50%|████▉     | 1994/4000 [13:45<12:29,  2.68it/s]

train:  57%|█████▋    | 1994/3515 [13:42<09:28,  2.68it/s]
overall:  50%|████▉     | 1995/4000 [13:45<12:19,  2.71it/s]

train:  57%|█████▋    | 1995/3515 [13:42<09:20,  2.71it/s]
overall:  50%|████▉     | 1996/4000 [13:45<12:19,  2.71it/s]

train:  57%|█████▋    | 1996/3515 [13:42<09:20,  2.71it/s]
overall:  50%|████▉     | 1997/4000 [13:46<12:22,  2.70it/s]

train:  57%|█████▋    | 1997/3515 [13:43<09:22,  2.70it/s]
overall:  50%|████▉     | 1998/4000 [13:46<12:23,  2.69it/s]

train:  57%|█████▋    | 1998/3515 [13:43<09:23,  2.69it/s]
overall:  50%|████▉     | 1999/4000 [13:46<12:25,  2.69it/s]

train:  57%|█████▋    | 1999/3515 [13:43<09:24,  2.69it/s]dev loss: 1.3059042692184448
dev per: 0.2663735691987513
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 0.8485530614852905
train per: 0.20220667384284177
train loss: 0.9518071413040161
train per: 0.22369048249563053
train loss: 0.8837839961051941
train per: 0.21191102607031811
train loss: 0.9056487083435059
train per: 0.2178578608765581
train loss: 0.891322135925293
train per: 0.21485993292562636
train loss: 0.8718636631965637
train per: 0.21092258748674445
train loss: 0.893377959728241
train per: 0.21177517880713387
train loss: 0.8497939109802246
train per: 0.2062231448848549
train loss: 0.8603782653808594
train per: 0.20483544303797468
train loss: 0.8686073422431946
train per: 0.2126077172182886
train loss: 0.8665840029716492
train per: 0.2110831735915756
train loss: 0.8968669772148132
train per: 0.21214928211003584
train loss: 0.9035377502441406
train per: 0.21711501800466004
train loss: 0.8838428258895874
train per: 0.21073486092646176
train loss: 0.940656304359436
train per: 0.2152840289951201
train loss: 0.8387693166732788
train per: 0.20201973194341027
train loss: 0.9061993360519409
train per: 0.21021455478517223
train loss: 0.8967427015304565
train per: 0.21572483820065405
train loss: 0.8735858798027039
train per: 0.2110012146451501
train loss: 0.8682258725166321
train per: 0.2065126167962849
train loss: 0.8522453308105469
train per: 0.20495930754783745
train loss: 0.8723638653755188
train per: 0.2059964461796431
train loss: 0.8136371374130249
train per: 0.19458046767537826
train loss: 0.8323270082473755
train per: 0.20151886462176502
train loss: 0.8996273279190063
train per: 0.2145249614546228
train loss: 0.9089161157608032
train per: 0.21237649505980238
train loss: 0.8713962435722351
train per: 0.2128380285665895
train loss: 0.8746255040168762
train per: 0.2107547514619883
train loss: 0.8308069109916687
train per: 0.20273607269853813
train loss: 0.8275898694992065
train per: 0.20033992958601432
train loss: 0.8824684023857117
train per: 0.20528626546631779
train loss: 0.8357707262039185
train per: 0.19729013549322533
train loss: 0.8539844751358032
train per: 0.20321697633293767
train loss: 0.827471137046814
train per: 0.203094226184306
train loss: 0.8502202033996582
train per: 0.20256416652116435
train loss: 0.7854371070861816
train per: 0.19274457634056488
train loss: 0.7912596464157104
train per: 0.1924971031286211
train loss: 0.8440841436386108
train per: 0.20262032348458778
train loss: 0.8589412569999695
train per: 0.2032387614976033
train loss: 0.8781061172485352
train per: 0.2067886645508362
train loss: 0.8317618370056152
train per: 0.20004727573572864
train loss: 0.8165236711502075
train per: 0.1922079902409271
train loss: 0.8525708913803101
train per: 0.20514307323837136
train loss: 0.8457673192024231
train per: 0.20219864502109167
train loss: 0.8572433590888977
train per: 0.2074613741992212
train loss: 0.8051885366439819
train per: 0.19303858366208024
train loss: 0.8378053903579712
train per: 0.20162286117481037
train loss: 0.8579079508781433
train per: 0.20621227302720008
train loss: 0.8285512924194336
train per: 0.20245339747444377
train loss: 0.8785347938537598
train per: 0.2076561852585056
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  10%|█         | 279/2703 [00:00<00:00, 2783.28it/s]


word -> phonemes:  21%|██        | 558/2703 [00:00<00:00, 2777.99it/s]


word -> phonemes:  31%|███▏      | 846/2703 [00:00<00:00, 2820.46it/s]


word -> phonemes:  42%|████▏     | 1129/2703 [00:00<00:00, 2708.88it/s]


word -> phonemes:  52%|█████▏    | 1403/2703 [00:00<00:00, 2719.20it/s]


word -> phonemes:  63%|██████▎   | 1692/2703 [00:00<00:00, 2773.05it/s]


word -> phonemes:  73%|███████▎  | 1974/2703 [00:00<00:00, 2784.57it/s]


word -> phonemes:  83%|████████▎ | 2255/2703 [00:00<00:00, 2792.51it/s]


word -> phonemes:  94%|█████████▍| 2535/2703 [00:00<00:00, 2774.60it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 2763.16it/s]



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overall:  50%|█████     | 2010/4000 [16:21<54:34,  1.65s/it]  

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train:  85%|████████▌ | 2994/3515 [21:55<02:50,  3.06it/s]
overall:  75%|███████▍  | 2995/4000 [21:58<05:43,  2.92it/s]

train:  85%|████████▌ | 2995/3515 [21:55<02:57,  2.92it/s]
overall:  75%|███████▍  | 2996/4000 [21:59<05:48,  2.88it/s]

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train:  85%|████████▌ | 2997/3515 [21:56<03:04,  2.81it/s]
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train:  85%|████████▌ | 2999/3515 [21:57<03:02,  2.83it/s]dev loss: 1.2960904836654663
dev per: 0.26234131113423514
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 0.7999361753463745
train per: 0.1938192419825073
train loss: 0.8577402234077454
train per: 0.20142675159235668
train loss: 0.8451957702636719
train per: 0.2042373547998007
train loss: 0.8329707980155945
train per: 0.19940227136879857
train loss: 0.8654766082763672
train per: 0.20944496396941525
train loss: 0.8288766741752625
train per: 0.20253651037663337
train loss: 0.7977586388587952
train per: 0.19174948000924427
train loss: 0.8160155415534973
train per: 0.19817159292262654
train loss: 0.7893099784851074
train per: 0.19530642349470295
train loss: 0.8678297996520996
train per: 0.20509214008153145
train loss: 0.8956913948059082
train per: 0.21233299075025694
train loss: 0.7910959720611572
train per: 0.192696876374835
train loss: 0.86259526014328
train per: 0.2100496070453152
train loss: 0.8773236274719238
train per: 0.20991680847041028
train loss: 0.8577782511711121
train per: 0.20732083165406226
train loss: 0.8895092010498047
train per: 0.20470818523669707
train loss: 0.8312904238700867
train per: 0.2006942100949718
train loss: 0.8491878509521484
train per: 0.202992700729927
train loss: 0.838248610496521
train per: 0.2008420396070482
train loss: 0.8019365072250366
train per: 0.19515577789885583
train loss: 0.7841777205467224
train per: 0.19067357512953367
train loss: 0.8053843379020691
train per: 0.19184949737705764
train loss: 0.8577753901481628
train per: 0.2055688068928589
train loss: 0.9306491613388062
train per: 0.21467626554882216
train loss: 0.8641145825386047
train per: 0.20256868801820843
train loss: 0.8570214509963989
train per: 0.20731401853552642
train loss: 0.8576914072036743
train per: 0.20400525943157682
train loss: 0.87291020154953
train per: 0.20956364002821729
train loss: 0.8259655833244324
train per: 0.20032097719724495
train loss: 0.7910701036453247
train per: 0.19212888943549378
train loss: 0.861321747303009
train per: 0.20726624369008476
train loss: 0.862999439239502
train per: 0.20458353985225047
train loss: 0.847335159778595
train per: 0.2007424071991001
train loss: 0.811164379119873
train per: 0.19701611205949068
train loss: 0.8384140729904175
train per: 0.2010149642160052
train loss: 0.8257937431335449
train per: 0.19558744942362014
train loss: 0.8193073272705078
train per: 0.19532466088503447
train loss: 0.8283559083938599
train per: 0.20268327743172018
train loss: 0.8935819864273071
train per: 0.2113507556675063
train loss: 0.832689106464386
train per: 0.20295889874099837
train loss: 0.8078667521476746
train per: 0.1963262050745227
train loss: 0.8199995160102844
train per: 0.20252178027667214
train loss: 0.8622974157333374
train per: 0.2086286594761171
train loss: 0.8403936624526978
train per: 0.1967353735146454
train loss: 0.8301132917404175
train per: 0.2004849636277279
train loss: 0.8535976409912109
train per: 0.20564193806245326
train loss: 0.8195011019706726
train per: 0.20086708976468437
train loss: 0.8872097730636597
train per: 0.20763328645794785
train loss: 0.8124740719795227
train per: 0.19955930006480882
train loss: 0.828528881072998
train per: 0.20179793040428737
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:   8%|▊         | 203/2703 [00:00<00:01, 2025.09it/s]


word -> phonemes:  15%|█▌        | 406/2703 [00:00<00:01, 2020.73it/s]


word -> phonemes:  23%|██▎       | 609/2703 [00:00<00:01, 2004.78it/s]


word -> phonemes:  30%|██▉       | 810/2703 [00:00<00:00, 1997.22it/s]


word -> phonemes:  38%|███▊      | 1020/2703 [00:00<00:00, 2031.22it/s]


word -> phonemes:  45%|████▌     | 1225/2703 [00:00<00:00, 2035.33it/s]


word -> phonemes:  53%|█████▎    | 1441/2703 [00:00<00:00, 2072.76it/s]


word -> phonemes:  61%|██████    | 1649/2703 [00:00<00:00, 2032.66it/s]


word -> phonemes:  69%|██████▉   | 1860/2703 [00:00<00:00, 2053.59it/s]


word -> phonemes:  76%|███████▋  | 2066/2703 [00:01<00:00, 2026.60it/s]


word -> phonemes:  84%|████████▍ | 2276/2703 [00:01<00:00, 2047.68it/s]


word -> phonemes:  92%|█████████▏| 2481/2703 [00:01<00:00, 2022.37it/s]


word -> phonemes:  99%|█████████▉| 2684/2703 [00:01<00:00, 1960.32it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2011.89it/s]



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overall:  75%|███████▌  | 3000/4000 [24:39<13:21:42, 48.10s/it]

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overall:  75%|███████▌  | 3001/4000 [24:40<9:22:42, 33.80s/it] 

train:  85%|████████▌ | 3001/3515 [24:37<4:49:31, 33.80s/it]
overall:  75%|███████▌  | 3002/4000 [24:40<6:35:27, 23.77s/it]

train:  85%|████████▌ | 3002/3515 [24:37<3:23:16, 23.77s/it]
overall:  75%|███████▌  | 3003/4000 [24:40<4:38:25, 16.76s/it]

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overall:  88%|████████▊ | 3515/4000 [27:37<02:52,  2.82it/s]

train: 100%|██████████| 3515/3515 [27:34<00:00,  2.82it/s]403-128339-0009 Failed!!!
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/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
403-128339-0009 Failed!!!

train: 100%|██████████| 3515/3515 [27:34<00:00,  2.12it/s]
dev loss: 1.3172796964645386
dev per: 0.2643080124869927
train loss: 0.8718816637992859
train per: 0.20299727520435967
train loss: 0.8502982258796692
train per: 0.20158463385354142
train loss: 0.8293522000312805
train per: 0.2006700806275877
train loss: 0.8483683466911316
train per: 0.20364039545412546
train loss: 0.8710269927978516
train per: 0.2032641305652226
train loss: 0.8004105687141418
train per: 0.19393637650018342
train loss: 0.847996711730957
train per: 0.20420886621818093
train loss: 0.860160231590271
train per: 0.207906872117872
train loss: 0.8471790552139282
train per: 0.20117438672263607
train loss: 0.8344453573226929
train per: 0.19762380293951964
train loss: 0.8139360547065735
train per: 0.1996816747147212
train loss: 0.8597947359085083
train per: 0.20196727135466394
train loss: 0.8654459714889526
train per: 0.20382988198619462
train loss: 0.8303378224372864
train per: 0.19862135299775568
train loss: 0.806677520275116
train per: 0.2053650546440751
train loss: 0.883722186088562
train per: 0.2097671185262426
train loss: 0.8351569175720215
train per: 0.20403833491842857
train loss: 0.8338095545768738
train per: 0.20033349834553554
train loss: 0.8386497497558594
train per: 0.20334642732832778
train loss: 0.7817012667655945
train per: 0.18920854110727528
train loss: 0.8062065839767456
train per: 0.1968975619964424
train loss: 0.856523871421814
train per: 0.20126894606979204
train loss: 0.804670512676239
train per: 0.1926172764179945
train loss: 0.8100627064704895
train per: 0.1971600776381653
train loss: 0.8492960929870605
train per: 0.20389005707419647
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


word -> phonemes:   0%|          | 0/3515 [00:00<?, ?it/s]

word -> phonemes:   6%|▌         | 205/3515 [00:00<00:01, 2044.37it/s]

word -> phonemes:  12%|█▏        | 425/3515 [00:00<00:01, 2131.58it/s]

word -> phonemes:  19%|█▊        | 658/3515 [00:00<00:01, 2219.41it/s]

word -> phonemes:  26%|██▌       | 906/3515 [00:00<00:01, 2321.89it/s]

word -> phonemes:  32%|███▏      | 1139/3515 [00:00<00:01, 2264.63it/s]

word -> phonemes:  40%|███▉      | 1390/3515 [00:00<00:00, 2344.51it/s]

word -> phonemes:  46%|████▌     | 1625/3515 [00:00<00:00, 2280.13it/s]

word -> phonemes:  53%|█████▎    | 1854/3515 [00:00<00:00, 2237.60it/s]

word -> phonemes:  59%|█████▉    | 2090/3515 [00:00<00:00, 2272.30it/s]

word -> phonemes:  66%|██████▌   | 2318/3515 [00:01<00:00, 2226.66it/s]

word -> phonemes:  72%|███████▏  | 2542/3515 [00:01<00:00, 2149.84it/s]

word -> phonemes:  79%|███████▉  | 2774/3515 [00:01<00:00, 2197.53it/s]

word -> phonemes:  85%|████████▌ | 2995/3515 [00:01<00:00, 2179.63it/s]

word -> phonemes:  92%|█████████▏| 3230/3515 [00:01<00:00, 2226.35it/s]

word -> phonemes:  98%|█████████▊| 3454/3515 [00:01<00:00, 2206.71it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 2229.13it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:  88%|████████▊ | 3516/4000 [27:41<11:28,  1.42s/it]

train:   0%|          | 1/3515 [00:01<1:14:04,  1.26s/it]
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overall:  88%|████████▊ | 3518/4000 [27:41<06:40,  1.20it/s]

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overall:  88%|████████▊ | 3519/4000 [27:42<05:44,  1.40it/s]

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overall:  88%|████████▊ | 3520/4000 [27:42<04:46,  1.68it/s]

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overall:  88%|████████▊ | 3521/4000 [27:42<04:00,  1.99it/s]

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overall:  88%|████████▊ | 3523/4000 [27:43<03:07,  2.55it/s]

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overall:  88%|████████▊ | 3524/4000 [27:43<03:03,  2.59it/s]

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overall:  88%|████████▊ | 3525/4000 [27:43<02:46,  2.84it/s]

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overall:  88%|████████▊ | 3526/4000 [27:44<02:17,  3.46it/s]

train:   0%|          | 11/3515 [00:04<15:28,  3.77it/s]
overall:  88%|████████▊ | 3527/4000 [27:44<02:29,  3.17it/s]

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overall:  89%|████████▉ | 3568/4000 [27:58<02:00,  3.59it/s]

train:   2%|▏         | 53/3515 [00:18<16:03,  3.59it/s]
overall:  89%|████████▉ | 3569/4000 [27:58<02:09,  3.33it/s]

train:   2%|▏         | 54/3515 [00:18<17:20,  3.33it/s]
overall:  89%|████████▉ | 3570/4000 [27:58<02:14,  3.20it/s]

train:   2%|▏         | 55/3515 [00:18<18:01,  3.20it/s]
overall:  89%|████████▉ | 3571/4000 [27:59<02:21,  3.04it/s]

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overall:  89%|████████▉ | 3572/4000 [27:59<02:29,  2.86it/s]

train:   2%|▏         | 57/3515 [00:19<20:07,  2.86it/s]
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overall:  89%|████████▉ | 3574/4000 [28:00<02:30,  2.84it/s]

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overall:  89%|████████▉ | 3575/4000 [28:00<02:31,  2.81it/s]

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overall:  89%|████████▉ | 3576/4000 [28:01<02:50,  2.48it/s]

train:   2%|▏         | 61/3515 [00:21<23:10,  2.48it/s]
overall:  89%|████████▉ | 3577/4000 [28:01<02:41,  2.61it/s]

train:   2%|▏         | 62/3515 [00:21<22:01,  2.61it/s]
overall:  89%|████████▉ | 3578/4000 [28:01<02:39,  2.65it/s]

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overall:  90%|████████▉ | 3582/4000 [28:03<02:36,  2.67it/s]

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overall:  90%|████████▉ | 3583/4000 [28:03<02:32,  2.73it/s]

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overall:  90%|████████▉ | 3586/4000 [28:04<01:54,  3.61it/s]

train:   2%|▏         | 71/3515 [00:24<15:52,  3.61it/s]
overall:  90%|████████▉ | 3587/4000 [28:04<02:03,  3.35it/s]

train:   2%|▏         | 72/3515 [00:24<17:06,  3.35it/s]
overall:  90%|████████▉ | 3588/4000 [28:05<02:26,  2.82it/s]

train:   2%|▏         | 73/3515 [00:25<20:21,  2.82it/s]
overall:  90%|████████▉ | 3589/4000 [28:05<02:28,  2.76it/s]

train:   2%|▏         | 74/3515 [00:25<20:45,  2.76it/s]
overall:  90%|████████▉ | 3590/4000 [28:05<02:28,  2.77it/s]

train:   2%|▏         | 75/3515 [00:25<20:41,  2.77it/s]
overall:  90%|████████▉ | 3591/4000 [28:06<02:24,  2.83it/s]

train:   2%|▏         | 76/3515 [00:26<20:13,  2.83it/s]
overall:  90%|████████▉ | 3592/4000 [28:06<02:18,  2.94it/s]

train:   2%|▏         | 77/3515 [00:26<19:27,  2.94it/s]
overall:  90%|████████▉ | 3593/4000 [28:06<02:21,  2.87it/s]

train:   2%|▏         | 78/3515 [00:27<19:58,  2.87it/s]
overall:  90%|████████▉ | 3594/4000 [28:07<02:19,  2.90it/s]

train:   2%|▏         | 79/3515 [00:27<19:44,  2.90it/s]
overall:  90%|████████▉ | 3595/4000 [28:07<02:11,  3.08it/s]

train:   2%|▏         | 80/3515 [00:27<18:36,  3.08it/s]
overall:  90%|████████▉ | 3596/4000 [28:07<02:12,  3.04it/s]

train:   2%|▏         | 81/3515 [00:27<18:49,  3.04it/s]
overall:  90%|████████▉ | 3597/4000 [28:08<02:18,  2.92it/s]

train:   2%|▏         | 82/3515 [00:28<19:37,  2.92it/s]
overall:  90%|████████▉ | 3598/4000 [28:08<02:16,  2.93it/s]

train:   2%|▏         | 83/3515 [00:28<19:29,  2.93it/s]
overall:  90%|████████▉ | 3599/4000 [28:08<02:12,  3.03it/s]

train:   2%|▏         | 84/3515 [00:28<18:51,  3.03it/s]
overall:  90%|█████████ | 3600/4000 [28:09<02:35,  2.57it/s]

train:   2%|▏         | 85/3515 [00:29<22:12,  2.57it/s]
overall:  90%|█████████ | 3601/4000 [28:09<02:32,  2.62it/s]

train:   2%|▏         | 86/3515 [00:29<21:48,  2.62it/s]
overall:  90%|█████████ | 3602/4000 [28:10<02:28,  2.69it/s]

train:   2%|▏         | 87/3515 [00:30<21:15,  2.69it/s]
overall:  90%|█████████ | 3603/4000 [28:10<02:31,  2.62it/s]

train:   3%|▎         | 88/3515 [00:30<21:47,  2.62it/s]
overall:  90%|█████████ | 3604/4000 [28:10<02:29,  2.65it/s]

train:   3%|▎         | 89/3515 [00:30<21:31,  2.65it/s]
overall:  90%|█████████ | 3605/4000 [28:11<01:56,  3.40it/s]

train:   3%|▎         | 90/3515 [00:31<16:47,  3.40it/s]
overall:  90%|█████████ | 3606/4000 [28:11<01:56,  3.39it/s]

train:   3%|▎         | 91/3515 [00:31<16:50,  3.39it/s]
overall:  90%|█████████ | 3607/4000 [28:11<02:02,  3.20it/s]

train:   3%|▎         | 92/3515 [00:31<17:51,  3.20it/s]
overall:  90%|█████████ | 3608/4000 [28:11<02:00,  3.25it/s]

train:   3%|▎         | 93/3515 [00:32<17:31,  3.25it/s]
overall:  90%|█████████ | 3609/4000 [28:12<02:04,  3.15it/s]

train:   3%|▎         | 94/3515 [00:32<18:05,  3.15it/s]
overall:  90%|█████████ | 3610/4000 [28:12<02:08,  3.03it/s]

train:   3%|▎         | 95/3515 [00:32<18:46,  3.03it/s]
overall:  90%|█████████ | 3611/4000 [28:13<02:13,  2.90it/s]

train:   3%|▎         | 96/3515 [00:33<19:37,  2.90it/s]
overall:  90%|█████████ | 3612/4000 [28:13<02:30,  2.58it/s]

train:   3%|▎         | 97/3515 [00:33<22:05,  2.58it/s]
overall:  90%|█████████ | 3613/4000 [28:13<02:22,  2.71it/s]

train:   3%|▎         | 98/3515 [00:33<21:00,  2.71it/s]
overall:  90%|█████████ | 3614/4000 [28:14<02:21,  2.73it/s]

train:   3%|▎         | 99/3515 [00:34<20:49,  2.73it/s]
overall:  90%|█████████ | 3615/4000 [28:14<02:25,  2.65it/s]

train:   3%|▎         | 100/3515 [00:34<21:28,  2.65it/s]
overall:  90%|█████████ | 3616/4000 [28:15<02:24,  2.66it/s]

train:   3%|▎         | 101/3515 [00:35<21:23,  2.66it/s]
overall:  90%|█████████ | 3617/4000 [28:15<02:21,  2.70it/s]

train:   3%|▎         | 102/3515 [00:35<21:02,  2.70it/s]
overall:  90%|█████████ | 3618/4000 [28:15<02:21,  2.71it/s]

train:   3%|▎         | 103/3515 [00:35<21:01,  2.71it/s]
overall:  90%|█████████ | 3619/4000 [28:16<02:20,  2.72it/s]

train:   3%|▎         | 104/3515 [00:36<20:54,  2.72it/s]
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train:   3%|▎         | 105/3515 [00:36<21:00,  2.71it/s]
overall:  91%|█████████ | 3621/4000 [28:16<02:20,  2.69it/s]

train:   3%|▎         | 106/3515 [00:36<21:06,  2.69it/s]
overall:  91%|█████████ | 3622/4000 [28:17<02:17,  2.75it/s]

train:   3%|▎         | 107/3515 [00:37<20:41,  2.75it/s]
overall:  91%|█████████ | 3623/4000 [28:17<02:17,  2.74it/s]

train:   3%|▎         | 108/3515 [00:37<20:45,  2.74it/s]
overall:  91%|█████████ | 3624/4000 [28:18<02:30,  2.50it/s]

train:   3%|▎         | 109/3515 [00:38<22:40,  2.50it/s]
overall:  91%|█████████ | 3625/4000 [28:18<02:25,  2.58it/s]

train:   3%|▎         | 110/3515 [00:38<21:57,  2.58it/s]
overall:  91%|█████████ | 3626/4000 [28:18<02:16,  2.74it/s]

train:   3%|▎         | 111/3515 [00:38<20:44,  2.74it/s]
overall:  91%|█████████ | 3627/4000 [28:19<02:20,  2.66it/s]

train:   3%|▎         | 112/3515 [00:39<21:20,  2.66it/s]
overall:  91%|█████████ | 3628/4000 [28:19<01:54,  3.26it/s]

train:   3%|▎         | 113/3515 [00:39<17:24,  3.26it/s]
overall:  91%|█████████ | 3629/4000 [28:19<01:59,  3.10it/s]

train:   3%|▎         | 114/3515 [00:39<18:16,  3.10it/s]
overall:  91%|█████████ | 3630/4000 [28:19<02:02,  3.02it/s]

train:   3%|▎         | 115/3515 [00:40<18:47,  3.02it/s]
overall:  91%|█████████ | 3631/4000 [28:20<02:01,  3.04it/s]

train:   3%|▎         | 116/3515 [00:40<18:38,  3.04it/s]
overall:  91%|█████████ | 3632/4000 [28:20<02:06,  2.91it/s]

train:   3%|▎         | 117/3515 [00:40<19:26,  2.91it/s]
overall:  91%|█████████ | 3633/4000 [28:21<02:08,  2.85it/s]

train:   3%|▎         | 118/3515 [00:41<19:53,  2.85it/s]
overall:  91%|█████████ | 3634/4000 [28:21<02:09,  2.82it/s]

train:   3%|▎         | 119/3515 [00:41<20:02,  2.82it/s]
overall:  91%|█████████ | 3635/4000 [28:21<02:11,  2.78it/s]

train:   3%|▎         | 120/3515 [00:41<20:23,  2.78it/s]
overall:  91%|█████████ | 3636/4000 [28:22<02:23,  2.54it/s]

train:   3%|▎         | 121/3515 [00:42<22:16,  2.54it/s]
overall:  91%|█████████ | 3637/4000 [28:22<02:20,  2.59it/s]

train:   3%|▎         | 122/3515 [00:42<21:49,  2.59it/s]
overall:  91%|█████████ | 3638/4000 [28:22<02:16,  2.65it/s]

train:   3%|▎         | 123/3515 [00:43<21:20,  2.65it/s]
overall:  91%|█████████ | 3639/4000 [28:23<02:19,  2.59it/s]

train:   4%|▎         | 124/3515 [00:43<21:48,  2.59it/s]
overall:  91%|█████████ | 3640/4000 [28:23<02:15,  2.65it/s]

train:   4%|▎         | 125/3515 [00:43<21:18,  2.65it/s]
overall:  91%|█████████ | 3641/4000 [28:24<02:14,  2.66it/s]

train:   4%|▎         | 126/3515 [00:44<21:14,  2.66it/s]
overall:  91%|█████████ | 3642/4000 [28:24<02:13,  2.69it/s]

train:   4%|▎         | 127/3515 [00:44<20:59,  2.69it/s]
overall:  91%|█████████ | 3643/4000 [28:24<02:11,  2.71it/s]

train:   4%|▎         | 128/3515 [00:44<20:49,  2.71it/s]
overall:  91%|█████████ | 3644/4000 [28:25<02:10,  2.72it/s]

train:   4%|▎         | 129/3515 [00:45<20:44,  2.72it/s]
overall:  91%|█████████ | 3645/4000 [28:25<02:09,  2.74it/s]

train:   4%|▎         | 130/3515 [00:45<20:36,  2.74it/s]
overall:  91%|█████████ | 3646/4000 [28:25<02:10,  2.72it/s]

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train:   5%|▍         | 171/3515 [00:59<20:14,  2.75it/s]
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train:   5%|▌         | 191/3515 [01:06<19:19,  2.87it/s]
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train:   5%|▌         | 192/3515 [01:06<16:49,  3.29it/s]
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train:   5%|▌         | 193/3515 [01:06<18:31,  2.99it/s]
overall:  93%|█████████▎| 3709/4000 [28:46<01:34,  3.08it/s]

train:   6%|▌         | 194/3515 [01:06<17:59,  3.08it/s]
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train:   6%|▌         | 195/3515 [01:07<16:26,  3.37it/s]
overall:  93%|█████████▎| 3711/4000 [28:47<01:32,  3.14it/s]

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train:  14%|█▎        | 477/3515 [02:46<15:33,  3.25it/s]
overall: 100%|█████████▉| 3993/4000 [30:27<00:02,  3.03it/s]

train:  14%|█▎        | 478/3515 [02:47<16:43,  3.03it/s]
overall: 100%|█████████▉| 3994/4000 [30:27<00:01,  3.15it/s]

train:  14%|█▎        | 479/3515 [02:47<16:03,  3.15it/s]
overall: 100%|█████████▉| 3995/4000 [30:27<00:01,  3.87it/s]

train:  14%|█▎        | 480/3515 [02:47<13:03,  3.87it/s]
overall: 100%|█████████▉| 3996/4000 [30:28<00:01,  3.08it/s]

train:  14%|█▎        | 481/3515 [02:48<16:23,  3.08it/s]
overall: 100%|█████████▉| 3997/4000 [30:28<00:01,  3.00it/s]

train:  14%|█▎        | 482/3515 [02:48<16:52,  3.00it/s]
overall: 100%|█████████▉| 3998/4000 [30:28<00:00,  2.90it/s]

train:  14%|█▎        | 483/3515 [02:48<17:26,  2.90it/s]
overall: 100%|█████████▉| 3999/4000 [30:29<00:00,  2.94it/s]

train:  14%|█▍        | 484/3515 [02:49<17:11,  2.94it/s]train loss: 0.841180145740509
train per: 0.2014569836908573
train loss: 0.7941997647285461
train per: 0.19419935354241286
train loss: 0.8283766508102417
train per: 0.20202123055774762
train loss: 0.8817263841629028
train per: 0.20947990543735226
train loss: 0.8345298767089844
train per: 0.20447802824758476
train loss: 0.8367667198181152
train per: 0.2004316760940756
train loss: 0.8445355296134949
train per: 0.19926563396442915
train loss: 0.8341947793960571
train per: 0.20238399101536578
train loss: 0.8395717740058899
train per: 0.2060831465253719
train loss: 0.837001621723175
train per: 0.20408900820899376
train loss: 0.8531631231307983
train per: 0.2060071315166185
train loss: 0.8793169856071472
train per: 0.2072958500669344
train loss: 0.8025075197219849
train per: 0.19392564587271582
train loss: 0.854088306427002
train per: 0.20290271215641234
train loss: 0.876683235168457
train per: 0.20998637286915384
train loss: 0.8213645815849304
train per: 0.19615609211161042
train loss: 0.7976517081260681
train per: 0.19976848431111768
train loss: 0.8355510830879211
train per: 0.2036412035936683
train loss: 0.8301241993904114
train per: 0.20076972418216807
train loss: 0.7937479019165039
train per: 0.19149433345016942
train loss: 0.9048681259155273
train per: 0.20484839234839236
train loss: 0.8582695126533508
train per: 0.2014780498566071
train loss: 0.8450844883918762
train per: 0.20464240604370726
train loss: 0.8456541895866394
train per: 0.20334078972962458
train loss: 0.8236457705497742
train per: 0.19539802843414078
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  10%|█         | 271/2703 [00:00<00:00, 2706.58it/s]


word -> phonemes:  20%|██        | 542/2703 [00:00<00:00, 2510.44it/s]


word -> phonemes:  29%|██▉       | 794/2703 [00:00<00:00, 2462.88it/s]


word -> phonemes:  39%|███▉      | 1066/2703 [00:00<00:00, 2560.37it/s]


word -> phonemes:  49%|████▉     | 1329/2703 [00:00<00:00, 2582.64it/s]


word -> phonemes:  59%|█████▉    | 1593/2703 [00:00<00:00, 2600.16it/s]


word -> phonemes:  69%|██████▊   | 1857/2703 [00:00<00:00, 2610.64it/s]


word -> phonemes:  78%|███████▊  | 2119/2703 [00:00<00:00, 2516.34it/s]


word -> phonemes:  88%|████████▊ | 2372/2703 [00:00<00:00, 2509.10it/s]


word -> phonemes:  98%|█████████▊| 2646/2703 [00:01<00:00, 2577.58it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2562.56it/s]



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overall: 100%|█████████▉| 3999/4000 [33:17<00:00,  2.94it/s]

train:  14%|█▍        | 484/3515 [05:37<17:11,  2.94it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [33:17<00:00,  2.94it/s]

train:  14%|█▍        | 484/3515 [05:37<17:11,  2.94it/s]
overall: 100%|██████████| 4000/4000 [33:17<00:00, 50.80s/it]

train:  14%|█▍        | 485/3515 [05:37<42:45:32, 50.80s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [05:38<35:11,  1.43it/s]   

overall: 100%|██████████| 4000/4000 [33:17<00:00,  2.00it/s]
dev loss: 1.3545628786087036
dev per: 0.2627731529656608
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt